Search Results - (( developing forecasting techniques algorithm ) OR ( a simulation optimization algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…In making a forecast for energy demand, accuracy is the primary criteria in selecting among forecasting techniques. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…According to the simulated results, the proposed model can provide a statistical distribution of the forecasted quantity. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, it really demands skill and experience on the part of simulation engineer. Today, tremendous efforts are made to develop Automatic History Matching algorithms. …”
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Final Year Project -
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Artificial neural network technique for modeling of groundwater level in Langat Basin, Malaysia
Published 2016“…All models developed had shown acceptable results. Based on the observation, the feed-forward neural network model optimized with the Levenberg-Marquardt algorithms showed the most beneficial results with the minimum MSE value of (0.048) and maximum R value of (0.839), obtained for simulation of groundwater levels. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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A New Optimization Technique Of Support Vector Machine For Electricity Market Price Forecasting
Published 2019“…Hence, some researchers have developed complex procedures and techniques to produce more accurate forecast while considering significant feature selection as well as parameter optimization. …”
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Technical Report -
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Rainfall time series modeling for a mountainous region in West Iran
Published 2010“…This study gives attention to long-term rainfall modelling since long-term forecasting could provide better data for optimal management of a resource that is to be used over a substantial period of time. …”
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10
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…A feed forward Artificial Neural Network (ANN) and an Adaptive Neuro-Fuzzy Inferences System (ANFIS) reservoir inflow models were developed to investigate their potential in forecasting reservoir inflows. …”
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Automated time series forecasting
Published 2011“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Monograph -
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Solving a multi-period inventory routing problem with stochastic unstationary demand rates
Published 2022“…The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. …”
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Solving a multiperiod inv entory routing problem with stochastic unstationary demand rates
Published 2022“…The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. …”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…The uncertainties of the output power of wind turbine generators are modelled based upon the scenario-based method and data mining techniques. In the second step, a model developed in this work is proposed to simulate the medium term restructured power market. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…The other foremost contribution of the work is proposing a hybrid electricity price forecasting technique to provide more accurate forecasts. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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